The Roboflow API is a robust machine learning interface that allows developers to upload, annotate, train, and deploy computer vision models. Using Pipedream, you can create powerful, serverless workflows to automate tasks involving image and video processing. With the API, you can programmatically manage datasets, kick off model training, and utilize trained models to analyze new data.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
roboflow: {
type: "app",
app: "roboflow",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://api.roboflow.com/`,
params: {
api_key: `${this.roboflow.$auth.api_key}`,
},
})
},
})
Automated Image Processing Pipeline: Upload images to Roboflow, trigger a model to process them, and receive analyzed data. For example, integrate with Dropbox on Pipedream to watch for new image uploads, send them to Roboflow for annotation, and store the results in a Google Sheet.
Real-time Video Analysis Feedback Loop: Connect a video streaming service to Roboflow via Pipedream. As new video snippets are streamed, they're sent to Roboflow's API for analysis. The processed data could then trigger events in other apps, like sending alerts via Slack if a certain condition is met.
Scheduled Model Retraining and Evaluation: Set up a Pipedream workflow that periodically re-trains your Roboflow model with new data and evaluates its performance. This workflow could post the evaluation results to a GitHub repository as an issue to track model improvements over time.
Run inference on classification models hosted on Roboflow. See the documentation.
Run inference on your object detection models hosted on Roboflow. See the documentation.
Upload an image to a project on the Roboflow platform. See the documentation.
Roboflow uses API keys for authentication. When you connect your Roboflow account, Pipedream securely stores the keys so you can easily authenticate to Roboflow APIs in both code and no-code steps.
To retrieve your Private API Key,